In general, 1-dimensional NMR experiments are employed to study a sample of a biofluid. In an NMR spectrum recorded from the sample, NMR spin systems of compounds contained in the sample produce NMR signals (peaks). Through use of the shape and size of a peak or peaks belonging to the NMR spin systems of a particular compound, the concentration of this compound can be determined.
However, in a typical biofluid such as urine, numerous compounds which have relevant NMR spin systems are contained, and so their corresponding peaks overlap. The same applies in general to samples of other fluid classes. Further, peak positions of the same NMR spin systems may vary from sample to sample, depending on characteristics of the sample such as its pH, temperature, or concentration of substances (or metabolites) contained. This makes it difficult to attribute peaks found in the NMR spectrum to the correct NMR spin systems or compounds, respectively. Attributing a peak to an NMR spin system is therefore, as a rule, an experienced expert's job requiring plenty of time, and even an experienced expert may do a wrong assignment, leading to wrong qualitative or quantitative composition information.
In a procedure known as spiking, after having recorded an NMR spectrum of the sample, a compound of interest is enriched in a sample, and another NMR spectrum is recorded. By comparison of the NMR spectra of the original sample and the enriched sample, in particular the increase of particular peak intensities, a more reliable attribution of peaks may be achieved. However, this procedure is very elaborate, and changes the composition of the original sample.
There are also computer-assisted peak identification tools, however, these generally require high computational power or a long calculation time, and may not avoid occasional wrong peak allocations, leading to wrong “positive” results in chemical analysis. More specifically, BATMAN (the same stands for BQuant) uses the Monte Carlo Markov Chain algorithm to calculate a Bayesian model for each NMR spin system within a user's predefined ppm region, which requires considerable computational effort. Moreover, BATMAN (and BQuant) are not designed as fully automated assignment tools and they require each time, being built in databases for assigning and quantifying a metabolite. For BATMAN, running a small ppm range from one spectrum when fitting just two metabolites, takes on the order of half a minute, and for a typical data set of about 200 spectra, fitting about 25 metabolites may take several days with state of the art computer equipment.
In U.S. Pat. No. 7,191,069 B2 it is proposed to obtain an NMR test spectrum from a sample under a measured condition, such as a particular pH, and to use this measured condition for selecting a set of reference spectra of compounds suspected to be present in the sample from a library. By combing reference spectra from the set, a matching compound spectrum is produced, the peaks of which match the test spectrum's peaks. The compounds associated with the reference spectra used to produce the matching spectrum are considered indicative of the compounds contained in the sample.
US 2015/0099668 A1 discloses the use of 1H NMR spectroscopy for determining levels of biomarkers in a mammalian biological sample, and to compare these levels to one or more core biomarkers reference levels for characterizing metastatic disease.